random walk

VALIDATION OF RANDOM WALK HYPOTHESIS

DEPARTMENT OF BUSINESS AND INDUSTRIAL MANAGEMENT, VNSGU, SURAT Page 1

EFFICIENT MARKET HYPOTHESIS (EMH)

In finance, the efficient market hypothesis (EMH) asserts that financial markets are

"informationally efficient or the prices on traded assets, e.g., stocks, bonds, or property, already

reflect all the known information and therefore are unbiased in the sense that they reflect the

collective beliefs of all investors about future prospects

The efficient market hypothesis states that it is not possible to consistently outperform the market

by using any information that the market already knows, except through luck. Information or news

in the EMH is defined as anything that may affect prices that is unknowable in the present and thus

appears randomly in the future.

An issue that is the subject of intense debate among academics and financial professionals is the

Efficient Market Hypothesis (EMH).

The Efficient Market Hypothesis states that at any given time, security prices fully reflect all

available information. The implications of the efficient market hypothesis are truly profound. Most

individuals that buy and sell securities (stocks in particular), do so under the assumption that the

securities they are buying are worth more than the price that they are paying, while securities that

they are selling are worth less than the selling price. But if markets are efficient and current prices

fully reflect all information, then buying and selling securities in an attempt to outperform the

market will effectively be a game of chance rather than skill.

Under the efficient market hypothesis, any time you buy and sell securities, you are engaging in a

game of chance, not skill. If markets are efficient and current, it means that prices always reflect

all information, so there is no way you will ever be able to buy a stock at a bargain price.

This theory has been met with a lot of opposition, especially from the technical analysts. Their

argument against the efficient market theory is that, many investors base their expectations on past

prices, past earnings, track records and other indicators. Because stock prices are largely based on



investors expectations, many believe it only makes sense to believe that past prices influence

future prices.

ASSUMPTIONS

Beyond the normal utility maximizing agents, the efficient market hypothesis requires that agents

have rational expectations; that on average the population are correct (even if no one person is)

and whether new relevant information appears, the agents update their expectations appropriately.

Note that it is not required that the agents be rational (which is different from rational expectations;

rational agents act coldly and achieve what they set out to do). EMH allows that when faced with

new information, some investors may overreact and some may under react. All that is required by

the EMH is that investors' reactions be random and follow a normal distribution pattern so that the

net effect on market prices cannot be reliably exploited to make an abnormal profit, especially

when considering transaction costs (including commissions and spreads). Thus, any one person

can be wrong about the market indeed, everyone can be but the market as a whole is always

right.

There are three common forms in which the efficient market hypothesis is commonly stated

weak form efficiency, semi-strong form efficiency and strong form efficiency, each of which

have different implications for how markets work.

WEAK-FORM EFFICIENCY

No excess returns can be earned by using investment strategies based on historical share

prices or other financial data.

Therefore, there is no benefit-as far as forecasting the future is concerned-in examining the

historical sequence of prices

Weak-form efficiency implies that Technical analysis techniques will not be able to

consistently produce excess returns, though some forms of fundamental analysis may still

provide excess returns.



If there is no value in studying past prices and past prices changes, there is no value in

technical analysis.

In a weak-form efficient market current share prices are the best, unbiased, estimate of the

value of the security. Theoretical in nature, weak form efficiency advocates assert that

fundamental analysis can be used to identify stocks that are undervalued and overvalued.

Therefore, keen investors looking for profitable companies can earn profits by researching

financial statements.

This weak form of the efficient market hypothesis is popularly known as the random-walk

theory.

SEMI-STRONG FORM EFFICIENCY

The semi strong form of the efficient market hypothesis says that current prices of stocks

not only reflect all information content of historical prices but also reflect all publicly

available knowledge about the corporations being studied.

IN effect, the semi strong form of the efficient market hypothesis maintains that as soon as

information becomes public ally available, it is absorbed and reflected in stock prices.

Even if this adjustment is not the correct one immediately, it will in a very short time be

properly analyzes by the market. Thus the analyst would have great difficulty trying to

profit using fundamental analysis

Semi-strong form efficiency implies that Fundamental analysis techniques will not be able

to reliably produce excess returns.

The semi strong form says that efforts by analysts and investors to acquire and analyze

public information will not yield consistently superior returns to the analyst.

Examples of the type of public information that will not be of value on a consistent basis

to the analyst are corporate reports, corporate announcements, and information relating to

corporate dividend policy, forthcoming stock splits, and so forth.

To test for semi-strong form efficiency, the adjustments to previously unknown news must

be of a reasonable size and must be instantaneous. To test for this, consistent upward or

downward adjustments after the initial change must be looked for. If there are any such



adjustments it would suggest that investors had interpreted the information in a biased

fashion and hence in an inefficient manner.

STRONG-FORM EFFICIENCY

The strong form of the efficient-market hypothesis maintains that not only is publicly

available information useless to the investor or analyst but all information is useless.

Specifically, no information that is available is it public or inside, can be used to earn

consistently superior investment returns.

Share prices reflect all information and no one can earn excess returns.

If there are legal barriers to private information becoming public, as with insider trading

laws, strong-form efficiency is impossible, except in the case where the laws are

universally ignored. Studies on the U.S. stock market have shown that people do trade on

inside information.

To test for strong form efficiency, a market needs to exist where investors cannot

consistently earn excess returns over a long period of time. Even if some money managers

are consistently observed to beat the market, no refutation even of strong-form efficiency

follows: with tens of thousands of fund managers worldwide, even a normal distribution

of returns (as efficiency predicts) should be expected to produce a few dozen "star"

performers.

To test the strong form of efficient market hypothesis, event more indirect methods must

be used. For the stronger form as has been already mentioned, says that no type of

information is useful. This implies that not even security analysts and portfolio managers

who have access to information more quickly than the general investing public are able to

use this information to earn superior returns.



RANDOM WALK

Can a series of historical stock prices or rates of return be an aid in predicting future stock prices

or rates of return? This, in effect, is the question posed by the random walk theory.

The empirical evidence in the random walk literature existed before the theory was established.

That is to say, empirical results were discovered first, and then an attempt was made to develop a

theory that could possibly explain the results. After these initial occurrences, more results and

more theory were uncovered. This has led then to a diversity of theories, which are generally called

the random-walk theory.

The random walk hypothesis is a financial theory stating that stock market prices evolve according

to a random walk and thus the prices of the stock market cannot be predicted. It has been described

as 'jibing' with the efficient market hypothesis. Investors, economists, and other financial

behaviorists have historically accepted the random walk hypothesis. They have run several tests

and continue to believe that stock prices are completely random because of the efficiency of the

market.

RUNS TEST

Runs test is used to find out whether the series of price movements have occurred by chance or

not. The runs test is a statistical technique used to detect if a time series is random or not. It is a

non-parametric test so probability distribution of the series data need not be predefined.

A test whether a one-dimensional data sample is compatible with being a random sampling from

a given distribution. It is also used to test whether two data samples are compatible with being

random samplings of the same, unknown distribution.



One first forms the histogram of the difference between the two histograms to be compared, or of

the difference between the histogram and the function to be compared, and then one counts the

number of runs in the difference. This number is then compared with that expected under the null

hypothesis, which is such that all orderings of sign are equally probable ( Runs).

Runs test ignore the absolute values of the numbers in the series and observe only their sign. The

researchers then merely count the number of runs-consecutive sequences of signs-in the same

direction. For example, the sequence - - - + 0 + has four runs. Next, the actual number of runs

observed is compared with the number that is to be expected from a series of randomly generated

price changes. It has been founds that when this is done, no significant differences are observed.

These results the further strengthen the random work hypothesis.

The first step in the runs test is to compute the sequential differences (Yi - Yi-1). Positive values

indicate an increasing value and negative values indicate a decreasing value. The output shows a

table of:

1. Runs of length exactly I for I = 1, 2, ..., 10

2. Number of runs of length I

3. Expected number of runs of length I

4. Standard deviation of the number of runs of length I

5. a z-score where the z-score is defined to be

E.q.(1)

Where,

is the sample mean and S is the sample standard deviation.

The z-score column is compared to a standard normal table. That is, at the 5% significance level,

a z-score with an absolute value greater than 1.96 indicates non-randomness.



RUNS

A "run" is a series of similar responses. In any sequence of real numbers not containing

exact zeros, a run is a subsequence of consecutive numbers of the same sign, immediately

preceded and followed by numbers of the opposite sign, or by the beginning or end of the

sequence. The number of runs in a sequence is therefore one more than the number of sign

changes in the sequence.

The runs test is usually not as powerful as the Kolmogorov test or the test ( Chi-Square

Test),but it can be combined with the test since it is (asymptotically) independent of it.

Runs Test is a nonparametric test because no assumption is made about population distribution

parameters. Use this test when you want to determine if the order of responses above or below a

specified value is random. A run is a set of consecutive observations that are all either less than or

greater than a specified value

Suppose an interviewer selects 30 people at random and asks them each a question for which there

is four possible answers. Their responses are coded 0, 1, 2, 3. You wish to perform a runs test in

order to check the randomness of answers. Answers that are not in random order may indicate that

a gradual bias exists in the phrasing of the questions or that subjects are not being selected at

random

The one-sample runs test of significance is commonly used as a test of randomness in a sample.

Note that this is a necessary but not sufficient test for random sampling. A non-random availability

sample of, say, students in a class, may be a very biased representation of all students in a

university, yet within the class the order of sampling may be random and the sample may pass the

runs test. On the other hand, if a purportedly random sample fails the runs test, this indicates that

there are unusual, non-random periodicities in the order of the sample inconsistent with random

sampling.



INTRODUCTION TO NSE

NATIONAL STOCK EXCHANGE

The National Stock Exchange (NSE) is India's leading stock exchange covering various cities and

towns across the country. NSE was set up by leading institutions to provide a modern, fully

automated screen-based trading system with national reach. The Exchange has brought about

unparalleled transparency, speed & efficiency, safety and market integrity. It has set up facilities

that serve as a model for the securities industry in terms of systems, practices and procedures.

NSE has played a catalytic role in reforming the Indian securities market in terms of

microstructure, market practices and trading volumes. The market today uses state-of-art

information technology to provide an efficient and transparent trading, clearing and settlement

mechanism, and has witnessed several innovations in products & services viz. demutualization of

stock exchange governance, screen based trading, compression of settlement cycles,

dematerialization and electronic transfer of securities, securities lending and borrowing,

professionalisation of trading members, fine-tuned risk management systems, emergence of

clearing corporations to assume counterpart risks, market of debt and derivative instruments and

intensive use of information technology.

THE ORGANIZATION

The National Stock Exchange of India Limited has genesis in the report of the High Powered Study

Group on Establishment of New Stock Exchanges, which recommended promotion of a National

Stock Exchange by financial institutions (FIs) to provide access to investors from all across the

country on an equal footing. Based on the recommendations, NSE was promoted by leading

Financial Institutions at the behest of the Government of India and was incorporated in November

1992 as a tax-paying company unlike other stock exchanges in the country.



On its recognition as a stock exchange under the Securities Contracts (Regulation) Act, 1956 in

April 1993, NSE commenced operations in the Wholesale Debt Market (WDM) segment in June

1994. The Capital Market (Equities) segment commenced operations in November 1994 and

operations in Derivatives segment commenced in June 2000.

S&P CNX NIFTY INDEX

S&P CNX Nifty is a well-diversified 50 stock index accounting for 22 sectors of the economy. It

is used for a variety of purposes such as benchmarking fund portfolios, index based derivatives

and index funds.

S&P CNX Nifty is owned and managed by India Index Services and Products Ltd. (IISL), which

is a joint venture between NSE and CRISIL. IISL is India's first specialized company focused upon

the index as a core product. IISL have a consulting and licensing agreement with Standard & Poor's

(S&P), who are world leaders in index services.

The average total traded value for the last six months of all Nifty stocks is approximately

45.24% of the traded value of all stocks on the NSE

Nifty stocks represent about 57.92% of the total market capitalization as on April 10, 2007.

Impact cost of the S&P CNX Nifty for a portfolio size of Rs.5 million is 0.08%

S&P CNX Nifty is professionally maintained and is ideal for derivatives trading

METHOD OF CALCULATION

S&P CNX Nifty is computed using market capitalization weighted method, wherein the level of

the index reflects the total market value of all the stocks in the index relative to a particular base

period. The method also takes into account constituent changes in the index and importantly

corporate actions such as stock splits, rights, etc without affecting the index value.



BASE DATA AND VALUE

The base period selected for S&P CNX Nifty index is the close of prices on November 3, 1995,

which marks the completion of one year of operations of NSE's Capital Market Segment. The base

value of the index has been set at 1000 and a base capital of Rs.2.06 trillion.

CRITERIA OF SELECTION OF CONSTITUENT STOCKS

The constituents and the criteria for the selection judge the effectiveness of the index. S&P CNX

Nifty is unique in this respect. Selection of the index set is based on 4 criteria:

1. Liquidity (Impact Cost)

2. Market Capitalization

3. Floating Stock

4. Others

LIQUIDITY (IMPACT COST)

For inclusion in the index, the security should have traded at an average impact cost of 0.75% or

less during the last six months for 90% of the observations (instead of the earlier criteria of 1.5%

or less during the last one year for 85% of the observations).

Impact cost is cost of executing a transaction in a security in proportion to the weight age of its

market capitalization as against the index market capitalization at any point of time. This is the

percentage mark up suffered while buying / selling the desired quantity of a security compared to

its ideal price (best buy + best sell)/2



For example, for the below order book:

Buy (Qty.) Buy (Price) Sell (Qty.) Sell (Price)

1000 98 1000 99

2000 97 1500 100

1000 96 1000 101

To Buy 1500 Shares:

Ideal Price = (99 + 98)/2 = 98.5

Actual Buy Price = (1000 X 99 + 500 X 100)/1500 = 99.33

(For 1500 shares) Impact Cost = [(99.33 - 98.5)/98.5] X 100 = 0.84%

MARKET CAPITALIZATION

Companies eligible for inclusion in Nifty must have a six monthly average market capitalization

of Rs.500 corers or more during the last six months.

FLOATING STOCK

Companies eligible for inclusion in S&P CNX Nifty should have at least 12% floating stock. For

this purpose, floating stock shall mean stocks which are not held by the promoters and associated

entities (where identifiable) of such companies.

OTHERS

A company which comes out with a IPO will be eligible for inclusion in the index, if it fulfills the

normal eligibility criteria for the index like impact cost, market capitalization and floating stock,

for a 3 month period instead of a 6 month period.



RESEARCH METHODOLOGY

RESEARCH STATEMENT

To check the randomness of daily price movement of 50 stocks listed on NSE.

RESEARCH OBJECTIVE

To find out the relevance of random walk hypothesis in the 50 companies listed on NSE.

To predict based on findings of the study, which companies to invest in and guide the

investors accordingly.

RESEARCH BENEFITS

This research can help in following ways:

It provides answer to the question that whether one can predict the prices of shares listed

companies on S&P CNX NIFTY through historical price movements.

It helps to guide investor to take better decisions regarding their investments.

The study will help to know the degree of relation of particular company to the nifty index.

This will also help them to take better decisions.



RESEARCH DESIGN

Research design is the plan and structure of investigation so as to obtain the answer to research

questions. The plan is the overall program of the research. It includes an outline of what the

investigation will do from writing the problems and their implication to final analysis of data.

Here descriptive research design is used. This project will describe the situation of the selected

companies listed in NSE that whether the share prices are random or not .

DATA COLLECTION

Secondary data are collected from books on research, marketing, past research reports and

websites.

SAMPLE PERIOD

The daily data of share prices of all 50 companies listed on S&P CNX NIFTY index starting from

1st January,2010 to 1st April,2015 is taken.

STATISTICAL TEST USED

Firstly return series are to be found out of the daily closing price of the companies by

using following equation.

1lnln ttt PPr E.q.(2)

Secondly, a runs test is performed by comparing the observed number of runs in the

sample against the sampling distribution under the random walk hypothesis.



HYPOTHESIS

Ho: The stock price series are random.

Alternative hypothesis

H1: The stock price series are not random.

STATISTICAL TOOL USED

SPSS software is used for testing the hypothesis using the runs test.

LIMITATIONS OF THE STUDY

There are constraints on adequate information available easily from government

and RBI websites.

The research solely depends on the data that the government makes available for

public use so the conclusion based on these findings may not be as accurate as it

would be if additional and exact data was available from government.

The information collected may not be sufficient and reliable when it is used from

sources other than government sources.



1. ACC LIMITED

Runs Test

ACC

Test Valuea .0000

Cases < Test Value 649

Cases >= Test Value 699

Total Cases 1348

Number of Runs 669

Z -.277

Asymp. Sig. (2-tailed) .782

INTERPRETATION :

From the above table we come to know that the significance value of runs test is 0.782 which is

more than the significance value 0.05 (0.782 > 0.05). Hence we fail to reject the null hypothesis at

5% level of significance. Thus the stock prices are random.



2. BHARTI AIRTEL

Runs Test

Airtel

Test Valuea .0000



Total Cases 1361

Number of Runs 714

Z 1.785


INTERPRETATION :






3. AMBUJA CEMENTS LIMITED.

Runs Test

AMBUJA

Test Valuea .0000



Total Cases 1361

Number of Runs 665

Z -.827


INTERPRETATION:






4. ASIAN PAINTS LIMITED

Runs Test

ASIAN PAINTS

Test Valuea .0000



Total Cases 1348

Number of Runs 648

Z -1.299


INTERPRETATION:






5. AXIS BANK LIMITED

Runs Test

AXIS

Test Valuea .0000



Total Cases 1347

Number of Runs 615

Z -3.139


INTERPRETATION:


less than the significance value 0.05 (0.002 < 0.05). Hence we reject the null hypothesis at 5%

level of significance. Thus the stock prices are not random.



6. BAJAJ AUTO LIMITED

Runs Test

BAJAJ

Test Valuea .0012



Total Cases 251

Number of Runs 130

Z .443


INTERPRETATION






7. BANK OF BARODA

Runs Test

BANK OF BARODA

Test Valuea .0000



Total Cases 1348

Number of Runs 673

Z .110


INTERPRETATION:






8. BHARAT PETROLEUM CORPORATION LIMITED

Runs Test

BHARAT PETROLEUM

Test Valuea .0000



Total Cases 1361

Number of Runs 702

Z 1.132


INTERPRETATION:






9. BHARAT HEAVY ELECTRICALS LIMITED

Runs Test

BHEL

Test Valuea .0000



Total Cases 1348

Number of Runs 634

Z -2.190


INTERPRETATION:






10. CAIRN INDIA LIMITED

Runs Test

CAIRN

Test Valuea .0000



Total Cases 1348

Number of Runs 694

Z 1.059


INTERPRETATION:






11. CIPLA LIMITED

Runs Test

CIPLA

Test Valuea .0000



Total Cases 1361

Number of Runs 718

Z 2.026


INTERPRETATION:






12. COAL INDIA LIMITED

Runs Test

Coal India

Test Valuea .0000



Total Cases 1135

Number of Runs 547

Z -1.103


INTERPRETATION:






13. DR. REDDYS LABORATORIES LIMITED

Runs Test

Dr.Reddy

Test Valuea .0003



Total Cases 1348

Number of Runs 690

Z .817


INTERPRETATION:






14. GAIL (INDIA) LIMITED.

Runs Test

GAIL

Test Valuea .0000



Total Cases 1348

Number of Runs 654

Z -1.083


INTERPRETATION:






15. GRASIM INDUSTRIES LIMITED.

Runs Test

Grasim

Test Valuea .0000



Total Cases 1348

Number of Runs 671

Z -.135


INTERPRETATION:






16. HCL TECHNOLOGIES LIMITED

Runs Test

HCL

Test Valuea .0004



Total Cases 1361

Number of Runs 685

Z .190


INTERPRETATION:






17. HDFC BANK LIMITED.

Runs Test

HDFC

Test Valuea .0000



Total Cases 1348

Number of Runs 674

Z .045


INTERPRETATION:






18. HERO MOTORCORP LIMITED

Runs Test

HEROMOTOR

Test Valuea .0000



Total Cases 1341

Number of Runs 608

Z -2.908


INTERPRETATION:






19. HINDALCO INDUSTRIES LIMITED

Runs Test

Hindalco

Test Valuea .0000



Total Cases 1361

Number of Runs 677

Z -.230


INTERPRETATION:






20. ICICI BANK

Runs Test

ICICI

Test Valuea .0000



Total Cases 1356

Number of Runs 638

Z -2.164


INTERPRETATION:

From the above table we come to know that the significance value of runs test is 0.03 which is less

than the significance value 0.05 (0.03 < 0.05). Hence we reject the null hypothesis at 5% level of

significance. Thus the stock prices are not random.



21. IDBI BANK

Runs Test

Idbi bank

Test Valuea .0000



Total Cases 1361

Number of Runs 671

Z -.486


INTERPRETATION:






22. IDEA CELLULAR

Runs Test

Idea cellular

Test Valuea .0000



Total Cases 1348

Number of Runs 653

Z -.905


INTERPRETATION:






23. IDFC LIMITED

Runs Test

IDFC

Test Valuea .0000



Total Cases 1361

Number of Runs 651

Z -1.608


INTERPRETATION:






24. INFOSYS LIMITED

Runs Test

Infosys

Test Valuea .0000



Total Cases 1375

Number of Runs 654

Z -1.539


INTERPRETATION:






25. ITC LIMITED

Runs Test

ITC

Test Valuea .0006



Total Cases 1361

Number of Runs 691

Z .515


INTERPRETATION:






26. KOTAK MAHINDRA BANK

Runs Test

Kotak

Test Valuea .0000



Total Cases 1361

Number of Runs 689

Z .756


INTERPRETATION:






27. LARSEN AND TOUBRO LIMITED

Runs Test

L&T

Test Valuea .0000



Total Cases 1361

Number of Runs 623

Z -3.148


INTERPRETATION:






28. LUPIN LIMITED

Runs Test

Lupin

Test Valuea .0005



Total Cases 1356

Number of Runs 686

Z .380


INTERPRETATION:






29. MAHINDRA AND MAHINDRA LIMITED

Runs Test

Mahindra & Mahindra

Test Valuea .0013



Total Cases 1319

Number of Runs 678

Z .964


INTERPRETATION:






30. MARUTI SUZUKI INDIA LIMITED

Runs Test

Maruti

Test Valuea .0000



Total Cases 1361

Number of Runs 691

Z .543


INTERPRETATION:






31. NMDC LIMITED

Runs Test

NMDC

Test Valuea .0000



Total Cases 1348

Number of Runs 656

Z -1.030


INTERPRETATION:






32. NTPC LIMITED

Runs Test

NTPC

Test Valuea .00



Total Cases 1361

Number of Runs 680

Z -.060


INTERPRETATION:






33. OIL AND NATURAL GAS CORPORATION LIMITED.

Runs Test

ONGC

Test Valuea .0000



Total Cases 1352

Number of Runs 675

Z -.102


INTERPRETATION:






34. PUNJAB NATIONAL BANK

Runs Test

PNB

Test Valuea .00



Total Cases 1361

Number of Runs 649

Z -1.731


INTERPRETATION:






35. POWER GRID CORPORATION OF INDIA

Runs Test

Powergrid

Test Valuea .0000



Total Cases 1348

Number of Runs 695

Z 1.230


INTERPRETATION:






36. RELIANCE INDUSTRIES LIMITED

Runs Test

Reliance

Test Valuea .0000



Total Cases 1361

Number of Runs 690

Z .464


INTERPRETATION:






37. STATE BANK OF INDIA

Runs Test

SBI

Test Valuea .0000



Total Cases 1348

Number of Runs 627

Z -2.523


INTERPRETATION:






38. SUN PHARMACEUTICALS INDUSTRIES LIMITED.

Runs Test

Sun Pharma

Test Valuea .0002



Total Cases 1361

Number of Runs 696

Z .786


INTERPRETATION:


more than the significance value 0.05 (0.432> 0.05). Hence we fail to reject the null hypothesis at




39. TATA POWER COMPANY LIMITED.

Runs Test

Tata Power

Test Valuea .0000



Total Cases 1348

Number of Runs 673

Z -.105


INTERPRETATION:






40. TATA STEEL LIMITED.

Runs Test

Tata Steel

Test Valuea -.0002



Total Cases 1023

Number of Runs 511

Z -.094


INTERPRETATION:






41. TATA CONSULTANCY SERVICES

Runs Test

TCS

Test Valuea .0001



Total Cases 1284

Number of Runs 632

Z -.614


INTERPRETATION:






42. TECH MAHINDRA LIMITED

Runs Test

Tech Mahindra

Test Valuea .0001



Total Cases 1348

Number of Runs 659

Z -.872


INTERPRETATION:






43. ULTRA TECH CEMENT LIMITED

Runs Test

Ultra Tech Cement

Test Valuea .0000



Total Cases 1360

Number of Runs 671

Z -.329


INTERPRETATION:






44. HINDUSTAN UNILEVER LIMITED

Runs Test

HUL

Test Valuea .0001



Total Cases 236

Number of Runs 118

Z -.130


INTERPRETATION






45. INDUSIND BANK LIMITED

Runs Test

INDUS

Test Valuea .0023



Total Cases 252

Number of Runs 129

Z .252


INTERPRETATION






46. WIPRO LIMITED.

Runs Test

Wipro

Test Valuea .0003



Total Cases 1348

Number of Runs 667

Z -.436


INTERPRETATION:






47. YES BANK LIMITED.

Runs Test

Yes Bank

Test Valuea .0000



Total Cases 1348

Number of Runs 621

Z -2.791


INTERPRETATION:






48. ZEE ENTERTAINMENT LIMITED.

Runs Test

Zee Entertainment

Test Valuea .0000



Total Cases 1355

Number of Runs 647

Z -1.631


INTERPRETATION:






49. HOUSING DEVELOPMENT FINANCE CORPORATION LIMITED.

Runs Test

HOUSING

Test Valuea .0000



Total Cases 1369

Number of Runs 687

Z .170


INTERPRETATION






50. SESA STERLITE LIMITED

Runs Test

sesa

Test Valuea .0000



Total Cases 221

Number of Runs 112

Z .068


INTERPRETATION






S&P CNX NIFTY

Runs Test

VAR00001

Test Valuea .00



Total Cases 1314

Number of Runs 582

Z -4.195


INTERPRETATION






FINDINGS AND RECOMMENDATIONS

Investors can be benefited by the study. The study gives investors an idea about the

companies, which are preferable to them for investment. It helps them to find out the

companies where trends are repeated in future. It can be seen that the majority of the stocks

i.e. 41 are pursuing random walk. They cannot earn abnormal return from their investments

in those companies. This finding assists them to take wiser investment decisions.

The study identifies 8 companies, which do not follow random walk in the share prices.

There is a repetition of past trends in the companies. It is possible for them to safeguard

their investment by examining the past trends in these companies.

The 8 companies which do not follow random walk are :

1. AXIS BANK

2. BHARAT HEAVY ELECTRICALS LIMITED,

3. CIPLA

4. HERO MOTORS

5. ICICI

6. LARSEN & TOUBRO

7. STATE BANK OF INDIA

8. YES BANK.



CONCLUSION

Result on the test shows that the substantial number of selected stocks listed on NSE does not

follow random walk. This implies that these stocks can be predicted by using historical

information. In other words, technical analysis plays an important role in devising profitable

trading rules on the bases of historical information on share price.

However, the majority of stocks listed on NSE (S&PCNX NIFTY) do not reject the null

hypothesis. It means that Ho is accepted. This implies that stock prices for the majority of firms

listed on NSE cannot be predicted on the bases of historical information. In other worlds, historical

information on daily observations could not be utilized to predict future stock price.

Finally this analysis proves that the nifty market is not efficient yet, as in some companies the

share prices are still predictable from the past trend.

To conclude the report, the analysis suggests that NSE stock market of India is weak form

efficient. It implies the markets price can be predicted using past data.

random walk

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